Ajou CVPR Lab
RESEARCH AIMS
Welcome to the Ajou Computer Vision and Pattern Recognition (CVPR) Lab!
We are a team of enthusiastic researchers dedicated to studying cutting-edge algorithms of computer vision in Ajou University, Republic of Korea. We now focus on deep learning-based methods for computer vision, including classification, detection, and segmentation.
Join us as we explore the latest developments in this exciting field!
NEWS
News Highlight
One paper accepted at
CVPR 2024
(Feb. 27, 2024)
IPIU2024 우수논문상 (금상) 외 2건
(Feb.2, 2024)
BK21 교육부 장관상
졸업생 나재민박사
(Dec. 31, 2023)
One paper accepted at
NeurIPS 2023
(Sept. 22, 2023)
24년年 2학기 아주대학교 AI학과 석/박사 과정 모집 (아주대생 우대, 박사지원자 우대) - 지도교수에게 메일로 문의 후 면담
- 전형일정: https://grad.ajou.ac.kr/gs/admission/schedule.do(New) [Feb./2024] Ph.d student, Do's paper (Domain Adaptation from RGB to Thermal images) Accepted at CVPR 2024
- Title: D3T: Distinctive Dual-Domain Teacher Zigzagging Across RGB-Thermal Gap for Domain-Adaptive Object Detection
- Conf.: IEEE/CVF Conf. on Computer Vision and Pattern Recognition (CVPR), Seattle, WA, US, 2024(New) [Feb./2024] IPIU2024 우수논문상 (금상) 우승범, (은상) DO DINH PHAT, (우수포스터발표상) 한지수 수상
(New) [Dec./2023] 나재민 박사 BK21 교육부 장관상 수상
[Sept./2023] Dr. Na's paper (Semi-supervised Learning) Accepted at NeurIPS 2023
- Title: Switching Temporary Teachers for Semi-Supervised Semantic Segmentation
- Conf.: 37th Conference on Neural Information Processing Systems (NeurIPS), New Orleans, US, 2023
Research Highlight
DOMAIN ADAPTATION
Domain Adaption aims to adapt models from a labeled source domain to a different but target domain without labels.
(New)[CVPR'24]
https://arxiv.org/abs/2403.09359[ECCV'22] https://arxiv.org/abs/2111.13353
[CVPR'21] https://arxiv.org/abs/2011.09230
SEMANTIC SEGMENTATION
Semantic Segmentation is the task of clustering parts of an image together which belong to the same object class.
(New) [NeurIPS'23]
https://arxiv.org/abs/2310.18640[CVPR'22] https://arxiv.org/abs/2111.14173
KNOWLEDGE DISTILLATION
Knowledge Distillation extracts pivtoal knowledge from a teacher network to guide the learning of a student network.
[ICCV'23]
https://arxiv.org/abs/2206.01186[CVPR'23] https://arxiv.org/abs/2205.15531
[ICCV'21] https://arxiv.org/abs/2009.08825
CONTINUAL LEARNING
Continual Learning is a model learning a large number of tasks sequentially without forgetting knowledge obtained from the preceding tasks.
SELF-SUPERVISED LEARNING
Self-supervised Learning for leveraging training data without supervision signals for Classification and Detection.
Demo & Presentation Highlight
913 Paldal hall, San 5-1, Woncheon-dong, Yeongtong-gu, Suwon-si, Gyeonggi-do, 16499, Republic of Korea